[1]刘强强,余黎青,赵鹏,等. 基于移动平台的图像检索系统[J].计算机技术与发展,2016,26(11):10-13.
 LIU Qiang-qiang,YU Li-qing,ZHAO Peng,et al. A Novel Image Retrieval System Based on Mobile Platform[J].,2016,26(11):10-13.
点击复制

 基于移动平台的图像检索系统()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年11期
页码:
10-13
栏目:
智能、算法、系统工程
出版日期:
2016-11-10

文章信息/Info

Title:
 A Novel Image Retrieval System Based on Mobile Platform
文章编号:
1673-629X(2016)11-0010-04
作者:
 刘强强余黎青赵鹏刘慧婷
 安徽大学 计算机科学与技术学院
Author(s):
 LIU Qiang-qiang;YU Li-qing;ZHAO Peng;LIU Hui-ting
关键词:
 特征提取图像检索图像搜索引擎爬虫系统
Keywords:
 feature extractionimage retrievalimage search enginespider system
分类号:
TP391.41
文献标志码:
A
摘要:
 近年来移动终端的普及促进了移动平台上图像检索技术的发展。当用户看到感兴趣的商品的时候,他们希望能够使用终端拍下来,然后进行商品的检索并返回一些推荐的商家。为了解决这个问题,面向移动平台,构建了一个图像检索系统,通过手机等移动终端,拍摄或传输图片来检索互联网上相关的图片和信息。该系统构建了一个爬虫系统用来采集图片信息,在安卓平台上直接进行图像特征提取,通过移动终端拍摄的商品图像搜索互联网图像,返回相关网店链接并进行相关商品推荐。该系统对120万幅图片采用位置敏感哈希索引、存储和检索,既保证了结果在较小的误差范围内,也极大地降低了时间复杂度。最后用户可以根据推荐的链接进行选购。实验结果表明,该系统能够满足用户的需求,并且具有很强的实用性。
Abstract:
 The popularity of mobile device in recent years promotes the development of image retrieval technology in mobile platform. When users see some interesting commodities,they hope to take a photo about them and retrieve them to get some recommended shops. In order to solve this problem,a novel image retrieval system is built facing mobile platform. By taking or transferring picture with mobile platform like mobile phones,the relevant web or information including the similar picture with the proposed system is retrieved. In the proposed system,the image features are extracted on the Android platform. The web links including the similar image are returned,and recommends are given. In order to collect images,a crawling system is established. For 1. 2 million images,the proposed system adopts Location Sensitive Hash to index and store. The proposed system not only promotes the retrieval performance,but also reduces the time complexity greatly. Users can buy commodities according to the recommended links. The experimental results show the system can meet users’ needs and has very strong practicalities.

相似文献/References:

[1]田昕辉 李成基.带有短语切分的中文文本分类方法[J].计算机技术与发展,2010,(01):5.
 TIAN Xin-hui,LEE Sung-kee.Phrase Segmentation for Chinese Text Classification[J].,2010,(11):5.
[2]何小娜 逄焕利.基于二维直方图和改进蚁群聚类的图像分割[J].计算机技术与发展,2010,(03):128.
 HE Xiao-na,PANG Huan-li.Image Segmentation Based on Improved Ant Colony Clustering and Two- Dimensional Histogram[J].,2010,(11):128.
[3]罗林波 陈绮.氨基酸序列特征提取方法研究[J].计算机技术与发展,2010,(02):206.
 LUO Lin-bo,CHEN Qi.Research of Feature Extraction Methods of Amino Acid Sequence[J].,2010,(11):206.
[4]姜鹤 陈丽亚.SVM文本分类中一种新的特征提取方法[J].计算机技术与发展,2010,(03):17.
 JIANG He,CHEN Li-ya.A New Feature Selection Method in SVM Text Categorization[J].,2010,(11):17.
[5]毛雁明 兰美辉 王运琼 冯乔生.一种改进的基于Harris的角点检测方法[J].计算机技术与发展,2009,(05):130.
 MAO Yan-ming,LAN Mei-hui,WANG Yun-qiong,et al.An Improved Corner Detection Method Based on Harris[J].,2009,(11):130.
[6]赵辉 张鹏.网络异常的主动检测与特征分析[J].计算机技术与发展,2009,(08):159.
 ZHAO Hui,ZHANG Peng.Active Detection and Feature Analysis About Network Anomaly[J].,2009,(11):159.
[7]汤婷 吴小培 项明.指纹图像增强与特征提取[J].计算机技术与发展,2009,(01):81.
 TANG Ting,WU Xiao-pei,XIANG Ming.Fingerprint Image Enhancement and Minutiae Extraction[J].,2009,(11):81.
[8]张国富 凌捷 彭辉 谷保平.基于支持向量机的手写签名研究[J].计算机技术与发展,2008,(05):57.
 ZHANG Guo-fu,LING Jie,PENG Hui,et al.Research of Handwritten Signature Based on SVM[J].,2008,(11):57.
[9]黄国宏 刘刚.一种新的基于Fisher准则的线性特征提取方法[J].计算机技术与发展,2008,(05):227.
 HUANG Guo-hong,LIU Gang.A New Linear Feature Extraction Method Based on Fisher Criterion[J].,2008,(11):227.
[10]黄国宏 刘刚.一种新的基于DCT变换的线性判别分析[J].计算机技术与发展,2008,(06):97.
 HUANG Guo-hong,LIU Gang.A Novel Linear Discriminant Analysis Based on DCT[J].,2008,(11):97.
[11]李春生[],苏晓伟[],魏军[],等. 基于支持向量机的抽油机井功图识别研究[J].计算机技术与发展,2014,24(08):215.
 LI Chun-sheng[],SU Xiao-wei[],WEI Jun[],et al. Research on Diagrams Identification of Pumping Unit Based on Support Vector Machine[J].,2014,24(11):215.
[12]汪昡紫,孙宪坤,刘锴. 一种图像边缘检测算法的改进和实现[J].计算机技术与发展,2014,24(09):108.
 WANG Xuan-zi,SUN Xian-kun,LIU Kai. Improvement and Implementation for an Image Edge Detection Algorithm[J].,2014,24(11):108.
[13]高翔,刘秀鹏,冯天天,等. 基于无线体域网的康复监测系统设计[J].计算机技术与发展,2014,24(09):234.
 GAO Xiang,LIU Xiu-peng,FENG Tian-tian,et al. Monitoring System Design for Rehabilitating Training Based on Wireless Body Area Network[J].,2014,24(11):234.
[14]陆明星,刘政怡,刘锋,等. 一种基于指纹生物特征识别系统[J].计算机技术与发展,2014,24(10):225.
 LU Ming-xing,LIU Zheng-yi,LIU Feng,et al. A Recognition System Based on Fingerprint Characteristic[J].,2014,24(11):225.
[15]谭松,高珏,刘有科,等. 基于对角线偏移的SURF算子改进[J].计算机技术与发展,2014,24(11):1.
 TAN Song,GAO Jue,LIU You-ke,et al. An Improvement of SURF Based on Diagonal Offset[J].,2014,24(11):1.
[16]陈静,邱晓晖,孙娜. 基于二维Gabor小波与SPP算法的人脸识别研究[J].计算机技术与发展,2014,24(11):110.
 CHEN Jing,QIU Xiao-hui,SUN Na. Research on Face Recognition Based on 2 D Gabor Wavelet and SPP Algorithm[J].,2014,24(11):110.
[17]丁洁[][],荆晓远[],姚永芳[],等. 局部统计不相关非线性鉴别变换[J].计算机技术与发展,2014,24(12):105.
 DING Jie[][],JING Xiao-yuan[],YAO Yong-fang[],et al. Local Uncorrelated Non-linear Discriminant Transform[J].,2014,24(11):105.
[18]张华伟[],阮进勇[][],丁广太[]. 万向椭圆描述的Mean-Shift算法[J].计算机技术与发展,2015,25(01):11.
 ZHANG Hua-wei[],NGUYEN Tien-dung][],DING Guang-tai[]. Mean-Shift Algorithm Described by Irregular Ellipse[J].,2015,25(11):11.
[19]凌若冰[],荆晓远[],吴飞[],等. 基于流形学习的正交稀疏保留投影鉴别分析[J].计算机技术与发展,2015,25(01):66.
 LING Ruo-bing[],JING Xiao-yuan[],WU Fei[],et al. Orthogonal Sparsity Preserving Discriminant Analysis Based on Manifold Learning[J].,2015,25(11):66.
[20]黄蕾,邹海. 基于相位一致的多尺度金字塔图像特征提取[J].计算机技术与发展,2015,25(03):36.
 HUANG Lei,ZOU Hai. Image Feature Extraction Algorithm of Multi-scale Pyramid Based on Phase Congruency[J].,2015,25(11):36.

更新日期/Last Update: 2016-12-09